Video imaging systems have been proposed for use in vehicles to monitor a subject person, such as the driver of the vehicle. Some proposed video imaging systems include one or two cameras focused on the driver to capture images of the driver's face. The video images are processed generally using computer vision and pattern recognition techniques to determine various facial characteristics of the driver including position, orientation, and movement of the driver's eyes, face, and head. Some advanced eye monitoring systems process the captured images to determine eye closure, such as open, half-open (half-closed), and closed states of the eye(s).
By knowing the driver's facial characteristics, vehicle control systems can provide enhanced vehicle functions. For example, a vehicle control system can monitor one or both eyes of the subject driver and determine a condition in which the driver appears to be fatigued or drowsy based on simple statistical analysis of the cumulated results of open or closed state of the eye(s) over time. Standard human factor measures such as PerClos (percentage of eye closure) and AveClos (average of eye closure) could be used to determine the drowsiness state of the driver. For instance, if the AveClos value is determined to be above a certain threshold, the system may initiate countermeasure action(s) to alert the driver of the driver drowsy condition and/or attempt to awaken the driver.
In a typical driver eye state monitor system, the system generally detects the face of the subject driver, analyzes the facial characteristics to determine potential eye candidates, and then detects and tracks one or both eyes of the driver, before processing individual characteristics of the eye, such as eye closure state, eye gaze directivity, etc. In prior known approaches, it has been difficult to automatically detect an eye of an individual subject, due to variations in light and head rotation. In prior known conventional approaches, eye detection often suffers from false detections of eye patterns, and generally requires subject calibration and full visibility of the driver's face.
It is therefore desirable to provide for a cost affordable and effective method for monitoring the face of a subject and detecting the eye(s). In particular, it is desirable to provide for an eye monitoring system for detecting the eye(s) of a driver of a vehicle that overcomes drawbacks of prior known proposed eye detection approaches.